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research-tech

Technology research skill - triggered when researching technologies, comparing tools, or seeking latest best practices. Searches the web, reads documentation, and synthesizes findings.

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Overview

Technology research skill - triggered when researching technologies, comparing tools, or seeking latest best practices. Searches the web, reads documentation, and synthesizes findings.

Install command

npx skills add https://github.com/IbrahimBadawy/claude-system-design-plugin --skill research-tech

Copy and paste this command into Claude Code to install the skill

Source

IbrahimBadawy/claude-system-design-plugin

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UpdatedApril 13, 2026 at 09:03

SKILL.md

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name	research-tech
description	Technology research skill - triggered when researching technologies, comparing tools, or seeking latest best practices. Searches the web, reads documentation, and synthesizes findings.
allowed-tools	Read, Write, Glob, Grep, WebFetch, WebSearch, Agent

Technology Research Skill

You are researching technologies and best practices.

Research Process

Step 1: Define Research Scope

What exactly are we researching?
What decisions does this inform?
What criteria matter most? (performance, cost, team expertise, maturity)

Step 2: Search Strategy

Search in this order:

Official documentation of the technology
ByteByteGo / Alex Xu articles for system design context
Engineering blogs from major companies (Netflix, Uber, Stripe, Airbnb, Meta, Google)
Benchmark comparisons (recent, 2024-2026)
Community discussions (GitHub issues, Stack Overflow, HN)
Cloud provider docs (AWS, GCP, Azure) for managed service options

Step 3: Evaluation Criteria

For each technology, assess:

Performance: Throughput, latency, resource usage
Scalability: How it scales horizontally and vertically
Reliability: Fault tolerance, data durability
Maturity: Production battle-tested, stable API
Community: Active development, contributor count, issue response time
Cost: Licensing, infrastructure, operational overhead
Integration: How well it fits with existing stack
Team: Learning curve, hiring availability

Step 4: Synthesis

Compare options in a structured matrix
Identify clear winner or context-dependent recommendations
Note any emerging trends or upcoming changes
Provide actionable recommendation with justification

Common Research Topics

Database selection (SQL vs NoSQL vs NewSQL)
Message queue comparison (Kafka vs RabbitMQ vs Pulsar)
Caching solutions (Redis vs Memcached vs Valkey)
Search engines (Elasticsearch vs Meilisearch vs Typesense)
API styles (REST vs gRPC vs GraphQL)
Container orchestration (Kubernetes vs alternatives)
Observability stack (OpenTelemetry ecosystem)
CI/CD tools and practices
Authentication/authorization solutions
Vector databases for AI/ML
Serverless platforms

Output

Structured research report with comparison matrix and clear recommendation.

More from this repository

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design-system

IbrahimBadawy/claude-system-design-plugin

Comprehensive system design skill - triggered when designing new systems, features, or architectures. Uses the 4-step framework from Alex Xu with knowledge from DDIA, Clean Architecture, and distributed systems best practices. Scales depth to the project's Complexity level (Simple/Medium/Complex).

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knowledge-builder

IbrahimBadawy/claude-system-design-plugin

Domain knowledge builder skill - triggered when working with unfamiliar domains, researching new technologies, or when the user asks to build knowledge about a topic. Researches deeply from the web and official docs, organizes into structured knowledge files, supports importing documentation files, and distinguishes between GLOBAL knowledge (cross-project) and PROJECT-specific knowledge.

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project-manager

IbrahimBadawy/claude-system-design-plugin

Project management skill - triggered when managing projects, tracking progress, switching contexts between different system design projects. Projects live in projects/<name>/ at the workspace root (outside .claude/).

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frontend-design

IbrahimBadawy/claude-system-design-plugin

Frontend design skill - triggered when designing or implementing user interfaces. Produces a COMPLETE frontend: full page inventory, permission-aware UI, all UX states (empty/loading/error/partial/success), keyboard navigation, accessibility (WCAG 2.2 AA), dark mode, RTL, dashboards, admin panel, audit log UI. Selects the best UI library, enforces Rule 24 (UX Completeness) and Rule 25 (RBAC by Default).

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implement-system

IbrahimBadawy/claude-system-design-plugin

Implementation skill - triggered when coding, building, or implementing system designs. Writes REAL production code. Researches latest docs from the internet before using any framework or library. Supports full-stack implementation with user-chosen technologies. Uses milestone-based validation after each shippable slice.

2026-04-161

cross-platform

IbrahimBadawy/claude-system-design-plugin

Cross-platform and platform migration skill - triggered when building apps that target multiple platforms (web + mobile + desktop), when migrating between platforms, or when choosing a cross-platform strategy. Covers shared code, platform-specific adaptations, and migration patterns.

2026-04-131

Source

IbrahimBadawy

IbrahimBadawy/claude-system-design-plugin

View GitHub Repository View Creator Repositories

Install command

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Useful forSOC

Software DevelopersComputer and Mathematical Occupations15-1252L4

name	research-tech
description	Technology research skill - triggered when researching technologies, comparing tools, or seeking latest best practices. Searches the web, reads documentation, and synthesizes findings.
allowed-tools	Read, Write, Glob, Grep, WebFetch, WebSearch, Agent

Technology Research Skill

You are researching technologies and best practices.

Research Process

Step 1: Define Research Scope

What exactly are we researching?
What decisions does this inform?
What criteria matter most? (performance, cost, team expertise, maturity)

Step 2: Search Strategy

Search in this order:

Official documentation of the technology
ByteByteGo / Alex Xu articles for system design context
Engineering blogs from major companies (Netflix, Uber, Stripe, Airbnb, Meta, Google)
Benchmark comparisons (recent, 2024-2026)
Community discussions (GitHub issues, Stack Overflow, HN)
Cloud provider docs (AWS, GCP, Azure) for managed service options

Step 3: Evaluation Criteria

For each technology, assess:

Performance: Throughput, latency, resource usage
Scalability: How it scales horizontally and vertically
Reliability: Fault tolerance, data durability
Maturity: Production battle-tested, stable API
Community: Active development, contributor count, issue response time
Cost: Licensing, infrastructure, operational overhead
Integration: How well it fits with existing stack
Team: Learning curve, hiring availability

Step 4: Synthesis

Compare options in a structured matrix
Identify clear winner or context-dependent recommendations
Note any emerging trends or upcoming changes
Provide actionable recommendation with justification

Common Research Topics

Database selection (SQL vs NoSQL vs NewSQL)
Message queue comparison (Kafka vs RabbitMQ vs Pulsar)
Caching solutions (Redis vs Memcached vs Valkey)
Search engines (Elasticsearch vs Meilisearch vs Typesense)
API styles (REST vs gRPC vs GraphQL)
Container orchestration (Kubernetes vs alternatives)
Observability stack (OpenTelemetry ecosystem)
CI/CD tools and practices
Authentication/authorization solutions
Vector databases for AI/ML
Serverless platforms

Output

Structured research report with comparison matrix and clear recommendation.